Offer summary

Qualifications:

5+ years of experience in applied machine learning, with at least 2 years focused on NLP or conversational AI., Strong experience with large language models (LLMs) such as GPT and Claude, as well as agent orchestration., Proficient in Python and experienced with frameworks like PyTorch and TensorFlow., Familiarity with cloud deployment in environments like AWS, GCP, or Azure..

Key responsibilities:

Build agentic workflows using frameworks like LangGraph and MCP.

Analyze call data, including transcripts and audio, to enhance model performance and automation.

Develop and deploy NLP/LLM models for tasks such as conversation understanding and sentiment analysis.

Work on real-time and batch inference pipelines in cloud environments.

Job description

Requirements:

5+ years in applied ML, with at least 2 years in NLP or conversational AI.
Strong experience with LLMs (GPT, Claude, open-source) and agent orchestration.
Strong Python skills, experience with PyTorch, TensorFlow, or similar frameworks.
Cloud deployment experience.

Responsibilities:

Build agentic workflows using frameworks like LangGraph and MCP.
Analyze call data (transcripts, audio, metadata) to drive model improvements and automation coverage.
Develop and deploy NLP/LLM models for conversation understanding, sentiment analysis, and summarization.
Work on real-time and batch inference pipelines in cloud environments (AWS, GCP, or Azure).

Required profile